Reusing frames in camera animation

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Rendering an animation in a global illumination framework is a very costly process. Each frame has to be computed with high accuracy to avoid both noise in a single frame and ickering from frame to frame. Recently an ef cient solution has been
presented for camera animation, which reused the results computed in a frame for other frames via reprojection of the rst hits of primary rays. This solution, however, is biased since it does not take into account the different probability densities that generated the different contributions to a pixel. In this paper we present a correct, unbiased solution for frame reuse. We show how the different contributions can be combined into an unbiased solution using multiple importance sampling. The validity of our solution is tested with an animation using path-tracing technique, and the results are compared with both the classic independent approach and the previous unweighted, biased, solution
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